Perform data engineering with Azure Databricks

Data Scientist
Data Engineer

Learn how to use Azure Databricks to accelerate the setup of Databricks in Azure. You'll work with data in an Azure SQL Data Warehouse with the built-in connector services. Explore the data services available with Azure Data Factory. Build streamlined workflows, and work with the interactive analytics workspace powered by Apache Spark. This learning path can help you prepare for the Microsoft Certified: Azure Developer Associate certification.


You need an Azure subscription to complete these exercises. If you don't have an Azure subscription, create a free account and add a subscription before you begin. If you are a student, you can take advantage of the Azure for students offer.

Modules in this learning path

Learn the fundamentals of Azure Databricks and Apache Spark notebooks.

Learn how to access Azure SQL Data Warehouse from Azure Databricks by using the SQL Data Warehouse connector. This allows you to use Apache Spark with Azure Blob storage and PolyBase in SQL Data Warehouse to efficiently transfer large volumes of data between a Databricks cluster and a SQL Data Warehouse instance.

In this module, you use Azure Databricks to work with multiple data sources. Learn how to combine inputs from files and data stores, such as Azure SQL Database, and transform and store that data for advanced analytics.

Use Azure Databricks to work with multiple data sources, combining inputs from files and data stores such as Azure SQL Database, and transform and store that data for advanced analytics.

Learn the tools and techniques to do basic data transformations in Azure Databricks.

Learn how to perform advanced data transformations in Azure Databricks, and encapsulate transformation logic through user-defined functions (UDFs) and libraries.

Learn how to use Databricks Delta in Azure to manage the flow of data (a data pipeline) to and from a data lake. This system includes mechanisms to create, append, and upsert data to Apache Spark tables, taking advantage of built-in reliability and optimizations. Learn how Databricks Delta architecture helps speed up reads, and how it lets multiple writers modify a dataset simultaneously and see consistent views. Finally, implement a Lambda Architecture by processing batch and streaming data with Delta.

Learn how to analyze and process streaming data by using Azure Event Hubs, Spark Structured Streaming, and Databricks Delta.

Use Azure Databricks to create basic to advanced visualizations by using built-in charts and third-party libraries such as Matplotlib. Connect your Azure Databricks data to Power BI to create business-intelligence dashboards that can be shared with others.